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A screenshot of the network of predicted functional modules

A key feature of the biological organization in all organisms is the tendency of proteins that function
in common pathways to physically associate via stable protein-protein interactions (PPI) to form larger
macromolecular assemblies or complexes (sometimes known as molecular machines). These complexes
are often linked together by extended networks of weaker, transient PPI, to form extended networks or
neighbourhoods that integrate pathways mediating the major cellular processes, such as the control of
gene expression, synthesis and degradation of biomolecules, cell propagation and the maintenance of
genome integrity. As a consequence, the cell is increasingly viewed as an assembly of interconnected
functional modules the interacto which integrates and coordinates the cells biochemical activities,
behavior and responses to external and intrinsic signals.

Given their broad significance, systematic experimental analyses of PPI networks have become a major
experimental focus, particularly since the recent publication of large-scale interaction studies in the
important model eukaryotes S. cerevisiae, C. elegans, and D. melanogaster. For the most
part, high-throughput methods for measuring PPI based on protein over-expression, such as the yeast two-hybrid
assay, suffer from high rates of false discovery. To this end, we have developed rigorous and effective
high-throughput methods for systematic large-scale affinity purification and characterization of
endogenous protein complexes, and by inference networks of PPI, from E. coli. Our preliminary proteomic
studies of ~1000 tagged and purified gene products (~1/4 of the genome) have provided insight into the functions of
previously uncharacterized proteins and the overall topology of PPI networks that link a subset of
microbial protein complexes [1]. While the core components of these PPI networks are broadly conserved, our
initial analyses have uncovered evidence of significant functional diversification in cross-species projections.
This initial study reinforces the utility of combining proteomics and comparative genomics to define the
molecular architecture of biochemical systems from an evolutionary perspective.

A view of the predicted functional interaction network

Funded by the Canadian institute of Health
Research we are currently extending this work by
undertaking a complete genome-scale analysis of PPI, to identify the
entire collection of protein complexes in E. coli, and to examine
the conservation of interactions across evolution. In addition to
experimentally determining sets of PPI's, we are also adopting modern informatics
methods to predict linkages between genes to construct a network of 'functional
interactions'. These are being used to define functional modules (e.g. pathways)
and help extend interaction neighborhoods. Our aim is to integrate these datasets
together with previously constructed knowledgebases on E. coli [2] and other
types of metadata such as evolutionary profiles, to construct definitive, reliable
and biologically-relevant datasets that inform on the molecular basis of biochemical
systems within bacteria.

It is our hope that the provision of this resource to the microbiology, computation and structural biology
research communities will help drive further research into the biochemical mechanisms underlying bacterial cell
proliferation and homeostasis, further our understanding of the molecular basis of evolutionary adaptation,
including colonization of a human host, and identify novel drug targets. We plan to develop and
integrate new and exisiting tools to facilitate browsing of the data and would therefore welcome any
feedback that you may have on the database and website. We will also endaevour to make the datasets freely
available for download as they become available.